Combinatorial Computational Chemistry Approach to the Design of Metal Sulfide Catalysts for Co Hydrogenation Process

Introduction Recently, computational chemistry made great impacts on the catalyst design and development. However, the computational chemistry is mainly employed to clarify the atomistic mechanism of the well-known catalytic reactions and to obtain the electronic information on the catalysts of which property and reactivity are well known experimentally. We suggested that such traditional computational chemistry can not contribute to the design and development of new catalysts at all. Hence, we recently introduced a concept of combinatorial chemistry used in the drug development to computational chemistry and proposed a new concept "Combinatorial Computational Chemistry" . In this concept, the computational chemistry is employed to perform a high-throughput screening of the catalysts including active metals, supports, and additives. On the other hand, the synthesis of the high-quality transportation fuels is expected in terms of the high-efficient utilization of the energy and low environmental impact. The development of high-active and high-selective catalysts with highresistance to sulfur for methanol synthesis and Fischer-Tropsch synthesis is strongly demanded in order to advance the industry of the high-quality transportation fuels. Recently Koizumi and coworkers reported that a lot of metal sulfide catalysts have high activity for the CO hydrogenation process 4 and especially Rh sulfide has the highest activity and predominantly produces methanol . Moreover, they found that the Rh sulfide catalyst is not deactivated by the H2S, while regular methanol synthesis catalyst Cu/ZnO/Al2O3 is easily deactivated by the H2S . Moreover, they also reported that the products of the CO hydrogenation process are strongly depending on the metal species of the metal sulfide catalysts . For example, Rh and Pd sulfides selectively produce methanol in the CO hydrogenation, while Re and Os sulfides predominantly produce hydrocarbons. We have already applied our combinatorial computational chemistry approach to the design of the methanol synthesis catalysts based on the Cu/ZnO and the Fischer-Tropsch catalysts based on the supported Fe metals and have succeeded to propose new catalysts and additives . Hence, we have confirmed the applicability of our combinatorial computational chemistry approach to the catalyst design. In the present study, we applied our combinatorial computational chemistry based on the first-principles approach to the metal sulfide catalysts and investigated the dependency of the metal species in the metal sulfide catalysts to the CO hydrogenation process and its products on the electronic level.